测绘通报 ›› 2024, Vol. 0 ›› Issue (3): 118-122.doi: 10.13474/j.cnki.11-2246.2024.0320

• 技术交流 • 上一篇    下一篇

基于卷积神经网络和无人机倾斜摄影图像的单个高层建筑物高度测算方法

高桂棠1, 郗连霞2, 钟晓龙1   

  1. 1. 国核电力规划设计研究院有限公司勘测分公司, 北京 100095;
    2. 北京超图软件股份有限公司, 北京 100600
  • 收稿日期:2023-09-14 发布日期:2024-04-08
  • 作者简介:高桂棠(1982—),男,硕士,高级工程师,主要从事关于神经网络、图像识别技术在测量测绘中的应用研究。E-mail:274027793@qq.com

A method for calculating the height of a single tall building based on convolutional neural networks and drone oblique photography images

GAO Guitang1, XI Lianxia2, ZHONG Xiaolong1   

  1. 1. Survey Branch, National Nuclear Power Planning and Design Research Institute Co., Ltd., Beijing 100095, China;
    2. SuperMap Software Co., Ltd., Beijing 100600, China
  • Received:2023-09-14 Published:2024-04-08

摘要: 为了提升单个高层建筑物高度测算效果,本文提出了基于卷积神经网络的无人机倾斜摄影图像的单个高层建筑物高度测算方法。首先,采用无人机倾斜摄影技术采集高层建筑物图像;然后,在卷积神经网络中输入高层建筑物图像,对其展开增强处理,提高图像的清晰度;最后,通过波段转换指数和阴影指数计算阴影长度,以此为依据测算单个高层建筑物的高度。试验结果表明,本文方法的图像增强处理效果较好、高度测算精度和效率较好。

关键词: 卷积神经网络, 无人机倾斜摄影, 图像增强, 阴影提取, 高度测算

Abstract: In order to improve the height calculation effect of a single high-rise building, a method based on convolutional neural network for calculating the height of a single high-rise building using unmanned aerial vehicle oblique photography images is proposed. Firstly, drone tilt photography technology is used to capture images of high-rise buildings.Secondly, input high-rise building images into the convolutional neural network and perform enhancement processing on them to improve the clarity of the image.Finally, the shadow length is calculated using the band conversion index and shadow index, and the height of a single high-rise building is calculated based on this. The experimental results show that the proposed method has good image enhancement processing effect, high measurement accuracy, and efficiency.

Key words: convolutional neural network, drone tilt photography, image enhancement, shadow extraction, height measurement

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